Gossip: Identifying Central Individuals in a Social Network
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Abstract. Can we identify the members of a community who are best-placed to diffuse information simply by asking a random sample of in-dividuals? We show that boundedly-rational individuals can, simply by tracking sources of gossip, identify those who are most central in a network according to “diffusion centrality, ” which nests other standard centrality measures. Testing this prediction with data from 35 Indian villages, we find that respondents accurately nominate those who are diffusion central (not just those with many friends). Moreover, these nominees are more central in the network than traditional village leaders and geographically central individuals.
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Highly connected individuals possess outsized influence, and it is unlikely that their centrality is solely related to being a producer of higher-quality information.
“Highly connected individuals possess outsized influence, and it is unlikely that their centrality is solely related to being a producer of higher-quality information”
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Tibshirani, R. (1996) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1996.tb02080.x · Cited by 51,482 · see citing works
Rogers, E. M., Singhal, A., & Quinlan, M. M. (2019) · Routledge eBooks · doi:10.4324/9780203710753-35 · Cited by 37,557 · see citing works
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Kempe, D., Kleinberg, J. M., & Eva Tardos, D. (2003) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/956750.956769 · Cited by 7,541 · see citing works
Milgram, S. (1967) · PsycEXTRA Dataset · doi:10.1037/e400002009-005 · Cited by 5,528 · see citing works
Gluesing, J. C. (2012) · Sage eBooks · doi:10.4135/9781412994231.n14 · Cited by 3,259 · see citing works
Borgatti, S. P. (2005) · Social Networks · doi:10.1016/j.socnet.2004.11.008 · Cited by 3,191 · see citing works
Jackson, M. O. (2008) · Princeton University Press eBooks · doi:10.1515/9781400833993 · Cited by 2,746 · see citing works
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Roshwalb, I., Katz, E., & Lazarsfeld, P. F. (1956) · Journal of Marketing · doi:10.2307/1247718 · Cited by 1,894 · see citing works
Borgatti, S. P. (2005) · Cited by 1,732 · see citing works
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Ballester, C., Calvó‐Armengol, A., & Zénou, Y. (2006) · Econometrica · doi:10.1111/j.1468-0262.2006.00709.x · Cited by 1,298 · see citing works
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Self-citationKrackhardt, D. M. (1987) · Social Networks · doi:10.1016/0378-8733(87)90009-8 · Cited by 1,091 · see citing works
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Madeo, D., Mocenni, C., Moraes, J. C., Zubelli, J. P., & 3 Instituto Nacional de Matemática Pura e Aplicada, R. D. J. (2019) · Mathematical Biosciences & Engineering · doi:10.3934/mbe.2019264 · Cited by 4 · see citing works
Information Diffusion in Heterogeneous Groups
Larson, J. (2016) · Studies in computational intelligence · doi:10.1007/978-3-319-50901-3_36 · Cited by 4 · see citing works
A framework for optimal high-level descriptions in science and engineering - preliminary report.Preprint
Wolpert, D. H., Grochow, J. A., Libby, E., & DeDeo, S. (2014) · arXiv (Cornell University) · Cited by 4 · see citing works
Social Interaction and Technology Adoption: Experimental Evidence from Improved Cookstoves in MaliPreprint
Bonan, J., Battiston, P., Bleck, J., LeMay‐Boucher, P., Pareglio, S., Sarr, B. A., & Tavoni, M. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.3122557 · Cited by 4 · see citing works
Family Networks and Distributive Politics
Marcel Fafchamps, A., & Labonne, J. (2019) · Journal of the European Economic Association · doi:10.1093/jeea/jvz023 · Cited by 3 · see citing works
Eliciting real-life social networks: a guided tour
Brañas‐Garza, P., Jiménez, N., & Ponti, G. (2017) · Middlesex University Research Repository (Middlesex University Of London) · Cited by 3 · see citing works
From "In" to "Over": Behavioral Experiments on Whole-Network Computation
Dworkin, L., & Kearns, M. J. (2015) · Proceedings of the AAAI Conference on Human Computation and Crowdsourcing · doi:10.1609/hcomp.v3i1.13223 · Cited by 3 · see citing works
Graph-Based Ascent Algorithms for Function Maximization
Pydi, M. S., Jog, V., & Loh, P. (2018) · Allerton Conference on Communication, Control, and Computing · doi:10.1109/allerton.2018.8636074 · Cited by 3 · see citing works
Scalable Mining and Analysis of Protein-Protein Interaction Networks
Arifuzzaman, S., & Pandey, B. (2017) · IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) · doi:10.1109/dasc-picom-datacom-cyberscitec.2017.178 · Cited by 3 · see citing works
Chinese Technology Transfer to Local Farmers in the Russian Far East
Yi, F., Gudaj, R. T., Arefieva, V., Yanbykh, R., Николаевна, М. С., Potenko, T. A., Zhou, J., & ZUENKO, I. Y. (2020) · American Journal of Economics and Sociology · doi:10.1111/ajes.12364 · Cited by 3 · see citing works
Assessing the Accuracy of Interpersonal Judgments About Social NetworksPreprint
Mobasseri, S., Srivastava, S. B., & Carney, D. R. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2742395 · Cited by 3 · see citing works
Iterative Optimization of Structural Entropy for Enhanced Network Fragmentation Analysis
Özaydin, F., Lubashevskiy, V., & Ozaydin, S. Y. (2025) · Information · doi:10.3390/info16100828 · Cited by 2 · see citing works
- Authors
- Banerjee, A., Chandrasekhar, A., Duflo, E., & Jackson, M.
- Affiliations
- Santa Fe Institute (US)
- Venue
- National Bureau of Economic Research
- Publisher
- National Bureau of Economic Research
- Published
- 2014-08
- OpenAlex
- W2168342758
- Cited by
- 143
- References
- 32
- Citations by year
- 2026: 1 · 2025: 6 · 2024: 7 · 2023: 5 · 2022: 5 · 2021: 10 · 2020: 15 · 2019: 17 · 2018: 16 · 2017: 17 · 2016: 16 · 2015: 18 · 2014: 8 · 2012: 2
- Type
- report
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- National Bureau of Economic Research (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- arXiv (Cornell University) (submittedVersion)
- National Bureau of Economic Research (submittedVersion)
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Social Sciences › Sociology and Political Science › Social Capital and Networks
- Social Sciences › Decision Sciences › Management Science and Operations Research › Game Theory and Applications
- Keywords
- gossip, social network centrality, information dissemination, community leaders, social influence, Indian villages
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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